It is our long range objective to apply appropriate methods of statistics required for an in-depth analysis of morphometric measurements of the blood vessel network of the human conjunctiva to achieve the best possible clinical screening test for early detection of diabetes mellitus and to utilize the optimal combination of variables as an index of the progression and severity of the disease. A second important long-term objective is the analysis and interpretation of data obtained in a longitudinal study involving progressive changes in microvascular indices. New methods of variables selection and discriminant algorithms developed at the University of California, San Diego, are already in use and have yielded improvements in percent classified correctly as diabetics or non-diabetics. Techniques are being investigated which would allow inclusion of important non-continuous variables in the discriminant function, such as age, duration of disease, age at onset, insulin dose, fasting blood sugar, to mention just a few. A thorough investigation will be performed on the statistical correlations between conjunctival measurements, such as blood vessel length per unit area, vessel diameter distribution and spacing, with additional indices of vascular involvement; for example, nailfold microvessel measurements and retinal microvessels including data derived from fluorescein angiograms and, where available, histological data.